Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017

a systematic analysis for the Global Burden of Disease Study 2017

GBD 2017 Risk Factor Collaborators, Valery L Feigin, Yohannes Kinfu

Research output: Contribution to journalArticle

199 Citations (Scopus)

Abstract

Background: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk–outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk–outcome pairs, and new data on risk exposure levels and risk–outcome associations. Methods: We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk–outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings: In 2017, 34·1 million (95% uncertainty interval [UI] 33·3–35·0) deaths and 1·21 billion (1·14–1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6–62·4) of deaths and 48·3% (46·3–50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39–11·5) deaths and 218 million (198–237) DALYs, followed by smoking (7·10 million [6·83–7·37] deaths and 182 million [173–193] DALYs), high fasting plasma glucose (6·53 million [5·23–8·23] deaths and 171 million [144–201] DALYs), high body-mass index (BMI; 4·72 million [2·99–6·70] deaths and 148 million [98·6–202] DALYs), and short gestation for birthweight (1·43 million [1·36–1·51] deaths and 139 million [131–147] DALYs). In total, risk-attributable DALYs declined by 4·9% (3·3–6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. Interpretation: By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning.

Original languageEnglish
Pages (from-to)1923-1994
Number of pages72
JournalThe Lancet
Volume392
Issue number10159
DOIs
Publication statusPublished - 10 Nov 2018

Fingerprint

Quality-Adjusted Life Years
Global Burden of Disease
Demography
Population Growth
Unsafe Sex
Northern Africa
Middle East
Far East
Africa South of the Sahara
Smoking
Public Health
Oceania
Odds Ratio
Alcohols
Epidemiological Monitoring
Central Asia
Population
Blood Pressure
Hypertension
Benchmarking

Cite this

@article{458c80b8bf8c4b6b9d9e6ebe9e44618a,
title = "Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017",
abstract = "Background: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk–outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk–outcome pairs, and new data on risk exposure levels and risk–outcome associations. Methods: We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk–outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings: In 2017, 34·1 million (95{\%} uncertainty interval [UI] 33·3–35·0) deaths and 1·21 billion (1·14–1·28) DALYs were attributable to GBD risk factors. Globally, 61·0{\%} (59·6–62·4) of deaths and 48·3{\%} (46·3–50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39–11·5) deaths and 218 million (198–237) DALYs, followed by smoking (7·10 million [6·83–7·37] deaths and 182 million [173–193] DALYs), high fasting plasma glucose (6·53 million [5·23–8·23] deaths and 171 million [144–201] DALYs), high body-mass index (BMI; 4·72 million [2·99–6·70] deaths and 148 million [98·6–202] DALYs), and short gestation for birthweight (1·43 million [1·36–1·51] deaths and 139 million [131–147] DALYs). In total, risk-attributable DALYs declined by 4·9{\%} (3·3–6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5{\%} decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6{\%} increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. Interpretation: By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning.",
keywords = "Adolescent, Adult, Age Distribution, Aged, Aged, 80 and over, Child, Child, Preschool, Disabled Persons/statistics & numerical data, Environmental Exposure/adverse effects, Female, Global Burden of Disease/statistics & numerical data, Global Health/statistics & numerical data, Health Risk Behaviors, Humans, Infant, Infant, Newborn, Life Expectancy, Male, Metabolic Diseases/epidemiology, Middle Aged, Occupational Diseases/epidemiology, Occupational Exposure/adverse effects, Quality-Adjusted Life Years, Risk Assessment, Sex Distribution, Socioeconomic Factors, Young Adult",
author = "{GBD 2017 Risk Factor Collaborators} and Stanaway, {Jeffrey D.} and Ashkan Afshin and Emmanuela Gakidou and Lim, {Stephen S.} and Degu Abate and Abate, {Kalkidan Hassen} and Cristiana Abbafati and Nooshin Abbasi and Hedayat Abbastabar and Foad Abd-Allah and Jemal Abdela and Ahmed Abdelalim and Ibrahim Abdollahpour and Abdulkader, {Rizwan Suliankatchi} and Molla Abebe and Zegeye Abebe and Abera, {Semaw F.} and Abil, {Olifan Zewdie} and Abraha, {Haftom Niguse} and Abrham, {Aklilu Roba} and Abu-Raddad, {Laith Jamal} and Abu-Rmeileh, {Niveen ME} and Accrombessi, {Manfred Mario Kokou} and Dilaram Acharya and Pawan Acharya and Adamu, {Abdu A.} and Adane, {Akilew Awoke} and Adebayo, {Oladimeji M.} and Adedoyin, {Rufus Adesoji} and Victor Adekanmbi and Zanfina Ademi and Adetokunboh, {Olatunji O.} and Adib, {Mina G.} and Amha Admasie and Adsuar, {Jose C.} and Afanvi, {Kossivi Agbelenko} and Mohsen Afarideh and Gina Agarwal and Anju Aggarwal and Aghayan, {Sargis Aghasi} and Anurag Agrawal and Sutapa Agrawal and Alireza Ahmadi and Mehdi Ahmadi and Hamid Ahmadieh and Ahmed, {Muktar Beshir} and Aichour, {Amani Nidhal} and Ibtihel Aichour and Aichour, {Miloud Taki Eddine} and Akbari, {Mohammad Esmaeil} and Tomi Akinyemiju and Nadia Akseer and Ziyad Al-Aly and Ayman Al-Eyadhy and Al-Mekhlafi, {Hesham M.} and Fares Alahdab and Khurshid Alam and Samiah Alam and Tahiya Alam and Alaa Alashi and Alavian, {Seyed Moayed} and Alene, {Kefyalew Addis} and Komal Ali and Ali, {Syed Mustafa} and Mehran Alijanzadeh and Reza Alizadeh-Navaei and Aljunid, {Syed Mohamed} and Ala'a Alkerwi and Fran{\cc}ois Alla and Ubai Alsharif and Khalid Altirkawi and Nelson Alvis-Guzman and Amare, {Azmeraw T.} and Walid Ammar and Anber, {Nahla Hamed} and Anderson, {Jason A.} and Andrei, {Catalina Liliana} and Sofia Androudi and Animut, {Megbaru Debalkie} and Mina Anjomshoa and Ansha, {Mustafa Geleto} and Ant{\'o}, {Josep M.} and Antonio, {Carl Abelardo T.} and Palwasha Anwari and Appiah, {Lambert Tetteh} and Appiah, {Seth Christopher Yaw} and Jalal Arabloo and Olatunde Aremu and Johan {\"A}rnl{\"o}v and Al Artaman and Aryal, {Krishna K.} and Hamid Asayesh and Zerihun Ataro and Marcel Ausloos and Avokpaho, {Euripide F.G.A.} and Ashish Awasthi and {Ayala Quintanilla}, {Beatriz Paulina} and Rakesh Ayer and Ayuk, {Tambe B.} and Azzopardi, {Peter S.} and Arefeh Babazadeh and Hamid Badali and Alaa Badawi and Kalpana Balakrishnan and Bali, {Ayele Geleto} and Kylie Ball and Ballew, {Shoshana H.} and Maciej Banach and Banoub, {Joseph Adel Mattar} and Aleksandra Barac and Barker-Collo, {Suzanne Lyn} and B{\"a}rnighausen, {Till Winfried} and Barrero, {Lope H.} and Sanjay Basu and Baune, {Bernhard T.} and Shahrzad Bazargan-Hejazi and Neeraj Bedi and Ettore Beghi and Masoud Behzadifar and Meysam Behzadifar and Yannick B{\'e}jot and Bekele, {Bayu Begashaw} and Bekru, {Eyasu Tamru} and Ezra Belay and Belay, {Yihalem Abebe} and Bell, {Michelle L.} and Bello, {Aminu K.} and Bennett, {Derrick A.} and Bensenor, {Isabela M.} and Gilles Bergeron and Adugnaw Berhane and Eduardo Bernabe and Bernstein, {Robert S.} and Mircea Beuran and Tina Beyranvand and Neeraj Bhala and Ashish Bhalla and Suraj Bhattarai and Bhutta, {Zulfiqar A.} and Belete Biadgo and Ali Bijani and Boris Bikbov and Ver Bilano and Nigus Bililign and {Bin Sayeed}, {Muhammad Shahdaat} and Donal Bisanzio and Tuhin Biswas and Tone Bj{\o}rge and Blacker, {Brigette F.} and Archie Bleyer and Rohan Borschmann and Bou-Orm, {Ibrahim R.} and Soufiane Boufous and Rupert Bourne and Brady, {Oliver J.} and Michael Brauer and Alexandra Brazinova and Breitborde, {Nicholas J.K.} and Hermann Brenner and Briko, {Andrey Nikolaevich} and Gabrielle Britton and Traolach Brugha and Rachelle Buchbinder and Burnett, {Richard T.} and Reinhard Busse and Butt, {Zahid A.} and Cahill, {Leah E.} and Lucero Cahuana-Hurtado and Campos-Nonato, {Ismael R.} and Rosario C{\'a}rdenas and Giulia Carreras and Carrero, {Juan J.} and F{\'e}lix Carvalho and Casta{\~n}eda-Orjuela, {Carlos A.} and {Castillo Rivas}, Jacqueline and Franz Castro and Ferr{\'a}n Catal{\'a}-L{\'o}pez and Kate Causey and Cercy, {Kelly M.} and Ester Cerin and Yazan Chaiah and Chang, {Hsing Yi} and Chang, {Jung Chen} and Chang, {Kai Lan} and Charlson, {Fiona J.} and Aparajita Chattopadhyay and Chattu, {Vijay Kumar} and Chee, {Miao Li} and Cheng, {Ching Yu} and Adrienne Chew and Chiang, {Peggy Pei Chia} and Odgerel Chimed-Ochir and Chin, {Ken Lee} and Abdulaal Chitheer and Choi, {Jee Young J.} and Rajiv Chowdhury and Hanne Christensen and Christopher, {Devasahayam J.} and Chung, {Sheng Chia} and Cicuttini, {Flavia M.} and Massimo Cirillo and Cohen, {Aaron J.} and Daniel Collado-Mateo and Cyrus Cooper and Cooper, {Owen R.} and Josef Coresh and Leslie Cornaby and Cortesi, {Paolo Angelo} and Monica Cortinovis and Megan Costa and Ewerton Cousin and Criqui, {Michael H.} and Cromwell, {Elizabeth A.} and Cundiff, {David K.} and Daba, {Alemneh Kabeta} and Dachew, {Berihun Assefa} and Dadi, {Abel Fekadu} and Damasceno, {Albertino Antonio Moura} and Lalit Dandona and Rakhi Dandona and Darby, {Sarah C.} and Dargan, {Paul I.} and Ahmad Daryani and {Das Gupta}, Rajat and {Das Neves}, Jos{\'e} and Dasa, {Tamirat Tesfaye} and Dash, {Aditya Prasad} and Davitoiu, {Dragos Virgil} and Kairat Davletov and {De la Cruz-G{\'o}ngora}, Vanessa and {De La Hoz}, {Fernando Pio} and {De Leo}, Diego and {De Neve}, {Jan Walter} and Louisa Degenhardt and Selina Deiparine and Dellavalle, {Robert P.} and Aniruddha Deshpande and Demoz, {Gebre Teklemariam} and Edgar Denova-Guti{\'e}rrez and Kebede Deribe and Nikolaos Dervenis and {El Bcheraoui}, Charbel and Dharmaratne, {Samath D.} and Kara Estep and Islam, {Sheikh Mohammed Shariful} and Kairsten Fay and Feigin, {Valery L} and Giannina Ferrara and Foreman, {Kyle J.} and Nancy Fullman and William Gardner and Caitlin Hawley and Simon Hay and Thomas Hsiao and Chantal Huynh and Caleb Irvine and Spencer James and Kassebaum, {N. J.} and Kemp, {Grant R.} and Ibrahim Khalil and Krohn, {Kristopher J.} and Kyu, {Hmwe Hmwe} and Larson, {Samantha L.} and Lopez, {Alan D} and Rafael Lozano and Helena Manguerra and Ashley Marks and Millear, {Anoushka I.} and Miller-Petrie, {Molly K.} and Misganaw, {Awoke T.} and Ali Mokdad and Kate Muller and Mohsen Naghavi and Grant Nguyen and Minh Nguyen and Emma Nichols and Nixon, {Molly R.} and Elaine Nsoesie and Odell, {Christopher M.} and Olsen, {Helen E.} and Kanyin Ong and Paulson, {Katherine R.} and Purcell, {Caroline A.} and Reiner, {Robert C.} and Reitsma, {Marissa B} and Yesenia Rom{\'a}n and Roth, {Gregory A.} and Smith, {David L.} and Vollset, {Stein E} and Theo Vos and Whiteford, {Harvey A.} and Simon Yadgir and Zimsen, {Stephanie R. M.} and Christopher Murray and Shiferaw, {Mekonnen S.} and Fitsum Weldegebreal and Habtamu Mitiku and Bali, {Ayele Geleto} and Merhawi Tekle and Dasa, {Tamirat Tesfaye} and Kedir Roba and Helen Diro and Tilayie Gelano and Tewodros Hailegiyorgis and Tigist Tekalign and Gebremedhin, {A. T.} and Duken, {Eyasu Ejeta} and Hussen, {Mamusha A.} and Seid Mereta and Irvani, {Seyed S. N.} and Moghaddam, {Sahar S.} and Mehran Shams-Beyranvand and Hedyeh Ebrahimi and Bahram Mohajer and Farnam Mohebi and F. Pishgar and Alireza Esteghamati and Morsaleh Ganji and Mousavi, {Seyyed M.} and Sharareh Eskandarieh and Mohammad Sahraian and Nima Hafezi-Nejad and Arvin Haj-Mirzaian and Randah Hamadeh and Hosseini, {Seyed M.} and Mansournia, {Mohammad A.} and Yohannes Kinfu",
year = "2018",
month = "11",
day = "10",
doi = "10.1016/S0140-6736(18)32225-6",
language = "English",
volume = "392",
pages = "1923--1994",
journal = "Lancet",
issn = "0140-6736",
publisher = "Elsevier Limited",
number = "10159",

}

TY - JOUR

T1 - Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017

T2 - a systematic analysis for the Global Burden of Disease Study 2017

AU - GBD 2017 Risk Factor Collaborators

AU - Stanaway, Jeffrey D.

AU - Afshin, Ashkan

AU - Gakidou, Emmanuela

AU - Lim, Stephen S.

AU - Abate, Degu

AU - Abate, Kalkidan Hassen

AU - Abbafati, Cristiana

AU - Abbasi, Nooshin

AU - Abbastabar, Hedayat

AU - Abd-Allah, Foad

AU - Abdela, Jemal

AU - Abdelalim, Ahmed

AU - Abdollahpour, Ibrahim

AU - Abdulkader, Rizwan Suliankatchi

AU - Abebe, Molla

AU - Abebe, Zegeye

AU - Abera, Semaw F.

AU - Abil, Olifan Zewdie

AU - Abraha, Haftom Niguse

AU - Abrham, Aklilu Roba

AU - Abu-Raddad, Laith Jamal

AU - Abu-Rmeileh, Niveen ME

AU - Accrombessi, Manfred Mario Kokou

AU - Acharya, Dilaram

AU - Acharya, Pawan

AU - Adamu, Abdu A.

AU - Adane, Akilew Awoke

AU - Adebayo, Oladimeji M.

AU - Adedoyin, Rufus Adesoji

AU - Adekanmbi, Victor

AU - Ademi, Zanfina

AU - Adetokunboh, Olatunji O.

AU - Adib, Mina G.

AU - Admasie, Amha

AU - Adsuar, Jose C.

AU - Afanvi, Kossivi Agbelenko

AU - Afarideh, Mohsen

AU - Agarwal, Gina

AU - Aggarwal, Anju

AU - Aghayan, Sargis Aghasi

AU - Agrawal, Anurag

AU - Agrawal, Sutapa

AU - Ahmadi, Alireza

AU - Ahmadi, Mehdi

AU - Ahmadieh, Hamid

AU - Ahmed, Muktar Beshir

AU - Aichour, Amani Nidhal

AU - Aichour, Ibtihel

AU - Aichour, Miloud Taki Eddine

AU - Akbari, Mohammad Esmaeil

AU - Akinyemiju, Tomi

AU - Akseer, Nadia

AU - Al-Aly, Ziyad

AU - Al-Eyadhy, Ayman

AU - Al-Mekhlafi, Hesham M.

AU - Alahdab, Fares

AU - Alam, Khurshid

AU - Alam, Samiah

AU - Alam, Tahiya

AU - Alashi, Alaa

AU - Alavian, Seyed Moayed

AU - Alene, Kefyalew Addis

AU - Ali, Komal

AU - Ali, Syed Mustafa

AU - Alijanzadeh, Mehran

AU - Alizadeh-Navaei, Reza

AU - Aljunid, Syed Mohamed

AU - Alkerwi, Ala'a

AU - Alla, François

AU - Alsharif, Ubai

AU - Altirkawi, Khalid

AU - Alvis-Guzman, Nelson

AU - Amare, Azmeraw T.

AU - Ammar, Walid

AU - Anber, Nahla Hamed

AU - Anderson, Jason A.

AU - Andrei, Catalina Liliana

AU - Androudi, Sofia

AU - Animut, Megbaru Debalkie

AU - Anjomshoa, Mina

AU - Ansha, Mustafa Geleto

AU - Antó, Josep M.

AU - Antonio, Carl Abelardo T.

AU - Anwari, Palwasha

AU - Appiah, Lambert Tetteh

AU - Appiah, Seth Christopher Yaw

AU - Arabloo, Jalal

AU - Aremu, Olatunde

AU - Ärnlöv, Johan

AU - Artaman, Al

AU - Aryal, Krishna K.

AU - Asayesh, Hamid

AU - Ataro, Zerihun

AU - Ausloos, Marcel

AU - Avokpaho, Euripide F.G.A.

AU - Awasthi, Ashish

AU - Ayala Quintanilla, Beatriz Paulina

AU - Ayer, Rakesh

AU - Ayuk, Tambe B.

AU - Azzopardi, Peter S.

AU - Babazadeh, Arefeh

AU - Badali, Hamid

AU - Badawi, Alaa

AU - Balakrishnan, Kalpana

AU - Bali, Ayele Geleto

AU - Ball, Kylie

AU - Ballew, Shoshana H.

AU - Banach, Maciej

AU - Banoub, Joseph Adel Mattar

AU - Barac, Aleksandra

AU - Barker-Collo, Suzanne Lyn

AU - Bärnighausen, Till Winfried

AU - Barrero, Lope H.

AU - Basu, Sanjay

AU - Baune, Bernhard T.

AU - Bazargan-Hejazi, Shahrzad

AU - Bedi, Neeraj

AU - Beghi, Ettore

AU - Behzadifar, Masoud

AU - Behzadifar, Meysam

AU - Béjot, Yannick

AU - Bekele, Bayu Begashaw

AU - Bekru, Eyasu Tamru

AU - Belay, Ezra

AU - Belay, Yihalem Abebe

AU - Bell, Michelle L.

AU - Bello, Aminu K.

AU - Bennett, Derrick A.

AU - Bensenor, Isabela M.

AU - Bergeron, Gilles

AU - Berhane, Adugnaw

AU - Bernabe, Eduardo

AU - Bernstein, Robert S.

AU - Beuran, Mircea

AU - Beyranvand, Tina

AU - Bhala, Neeraj

AU - Bhalla, Ashish

AU - Bhattarai, Suraj

AU - Bhutta, Zulfiqar A.

AU - Biadgo, Belete

AU - Bijani, Ali

AU - Bikbov, Boris

AU - Bilano, Ver

AU - Bililign, Nigus

AU - Bin Sayeed, Muhammad Shahdaat

AU - Bisanzio, Donal

AU - Biswas, Tuhin

AU - Bjørge, Tone

AU - Blacker, Brigette F.

AU - Bleyer, Archie

AU - Borschmann, Rohan

AU - Bou-Orm, Ibrahim R.

AU - Boufous, Soufiane

AU - Bourne, Rupert

AU - Brady, Oliver J.

AU - Brauer, Michael

AU - Brazinova, Alexandra

AU - Breitborde, Nicholas J.K.

AU - Brenner, Hermann

AU - Briko, Andrey Nikolaevich

AU - Britton, Gabrielle

AU - Brugha, Traolach

AU - Buchbinder, Rachelle

AU - Burnett, Richard T.

AU - Busse, Reinhard

AU - Butt, Zahid A.

AU - Cahill, Leah E.

AU - Cahuana-Hurtado, Lucero

AU - Campos-Nonato, Ismael R.

AU - Cárdenas, Rosario

AU - Carreras, Giulia

AU - Carrero, Juan J.

AU - Carvalho, Félix

AU - Castañeda-Orjuela, Carlos A.

AU - Castillo Rivas, Jacqueline

AU - Castro, Franz

AU - Catalá-López, Ferrán

AU - Causey, Kate

AU - Cercy, Kelly M.

AU - Cerin, Ester

AU - Chaiah, Yazan

AU - Chang, Hsing Yi

AU - Chang, Jung Chen

AU - Chang, Kai Lan

AU - Charlson, Fiona J.

AU - Chattopadhyay, Aparajita

AU - Chattu, Vijay Kumar

AU - Chee, Miao Li

AU - Cheng, Ching Yu

AU - Chew, Adrienne

AU - Chiang, Peggy Pei Chia

AU - Chimed-Ochir, Odgerel

AU - Chin, Ken Lee

AU - Chitheer, Abdulaal

AU - Choi, Jee Young J.

AU - Chowdhury, Rajiv

AU - Christensen, Hanne

AU - Christopher, Devasahayam J.

AU - Chung, Sheng Chia

AU - Cicuttini, Flavia M.

AU - Cirillo, Massimo

AU - Cohen, Aaron J.

AU - Collado-Mateo, Daniel

AU - Cooper, Cyrus

AU - Cooper, Owen R.

AU - Coresh, Josef

AU - Cornaby, Leslie

AU - Cortesi, Paolo Angelo

AU - Cortinovis, Monica

AU - Costa, Megan

AU - Cousin, Ewerton

AU - Criqui, Michael H.

AU - Cromwell, Elizabeth A.

AU - Cundiff, David K.

AU - Daba, Alemneh Kabeta

AU - Dachew, Berihun Assefa

AU - Dadi, Abel Fekadu

AU - Damasceno, Albertino Antonio Moura

AU - Dandona, Lalit

AU - Dandona, Rakhi

AU - Darby, Sarah C.

AU - Dargan, Paul I.

AU - Daryani, Ahmad

AU - Das Gupta, Rajat

AU - Das Neves, José

AU - Dasa, Tamirat Tesfaye

AU - Dash, Aditya Prasad

AU - Davitoiu, Dragos Virgil

AU - Davletov, Kairat

AU - De la Cruz-Góngora, Vanessa

AU - De La Hoz, Fernando Pio

AU - De Leo, Diego

AU - De Neve, Jan Walter

AU - Degenhardt, Louisa

AU - Deiparine, Selina

AU - Dellavalle, Robert P.

AU - Deshpande, Aniruddha

AU - Demoz, Gebre Teklemariam

AU - Denova-Gutiérrez, Edgar

AU - Deribe, Kebede

AU - Dervenis, Nikolaos

AU - El Bcheraoui, Charbel

AU - Dharmaratne, Samath D.

AU - Estep, Kara

AU - Islam, Sheikh Mohammed Shariful

AU - Fay, Kairsten

AU - Feigin, Valery L

AU - Ferrara, Giannina

AU - Foreman, Kyle J.

AU - Fullman, Nancy

AU - Gardner, William

AU - Hawley, Caitlin

AU - Hay, Simon

AU - Hsiao, Thomas

AU - Huynh, Chantal

AU - Irvine, Caleb

AU - James, Spencer

AU - Kassebaum, N. J.

AU - Kemp, Grant R.

AU - Khalil, Ibrahim

AU - Krohn, Kristopher J.

AU - Kyu, Hmwe Hmwe

AU - Larson, Samantha L.

AU - Lopez, Alan D

AU - Lozano, Rafael

AU - Manguerra, Helena

AU - Marks, Ashley

AU - Millear, Anoushka I.

AU - Miller-Petrie, Molly K.

AU - Misganaw, Awoke T.

AU - Mokdad, Ali

AU - Muller, Kate

AU - Naghavi, Mohsen

AU - Nguyen, Grant

AU - Nguyen, Minh

AU - Nichols, Emma

AU - Nixon, Molly R.

AU - Nsoesie, Elaine

AU - Odell, Christopher M.

AU - Olsen, Helen E.

AU - Ong, Kanyin

AU - Paulson, Katherine R.

AU - Purcell, Caroline A.

AU - Reiner, Robert C.

AU - Reitsma, Marissa B

AU - Román , Yesenia

AU - Roth, Gregory A.

AU - Smith, David L.

AU - Vollset, Stein E

AU - Vos, Theo

AU - Whiteford, Harvey A.

AU - Yadgir, Simon

AU - Zimsen, Stephanie R. M.

AU - Murray, Christopher

AU - Shiferaw, Mekonnen S.

AU - Weldegebreal, Fitsum

AU - Mitiku, Habtamu

AU - Bali, Ayele Geleto

AU - Tekle, Merhawi

AU - Dasa, Tamirat Tesfaye

AU - Roba, Kedir

AU - Diro, Helen

AU - Gelano, Tilayie

AU - Hailegiyorgis, Tewodros

AU - Tekalign, Tigist

AU - Gebremedhin, A. T.

AU - Duken, Eyasu Ejeta

AU - Hussen, Mamusha A.

AU - Mereta, Seid

AU - Irvani, Seyed S. N.

AU - Moghaddam, Sahar S.

AU - Shams-Beyranvand, Mehran

AU - Ebrahimi, Hedyeh

AU - Mohajer, Bahram

AU - Mohebi, Farnam

AU - Pishgar, F.

AU - Esteghamati, Alireza

AU - Ganji, Morsaleh

AU - Mousavi, Seyyed M.

AU - Eskandarieh, Sharareh

AU - Sahraian, Mohammad

AU - Hafezi-Nejad, Nima

AU - Haj-Mirzaian, Arvin

AU - Hamadeh, Randah

AU - Hosseini, Seyed M.

AU - Mansournia, Mohammad A.

AU - Kinfu, Yohannes

PY - 2018/11/10

Y1 - 2018/11/10

N2 - Background: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk–outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk–outcome pairs, and new data on risk exposure levels and risk–outcome associations. Methods: We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk–outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings: In 2017, 34·1 million (95% uncertainty interval [UI] 33·3–35·0) deaths and 1·21 billion (1·14–1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6–62·4) of deaths and 48·3% (46·3–50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39–11·5) deaths and 218 million (198–237) DALYs, followed by smoking (7·10 million [6·83–7·37] deaths and 182 million [173–193] DALYs), high fasting plasma glucose (6·53 million [5·23–8·23] deaths and 171 million [144–201] DALYs), high body-mass index (BMI; 4·72 million [2·99–6·70] deaths and 148 million [98·6–202] DALYs), and short gestation for birthweight (1·43 million [1·36–1·51] deaths and 139 million [131–147] DALYs). In total, risk-attributable DALYs declined by 4·9% (3·3–6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. Interpretation: By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning.

AB - Background: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk–outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk–outcome pairs, and new data on risk exposure levels and risk–outcome associations. Methods: We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk–outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings: In 2017, 34·1 million (95% uncertainty interval [UI] 33·3–35·0) deaths and 1·21 billion (1·14–1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6–62·4) of deaths and 48·3% (46·3–50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39–11·5) deaths and 218 million (198–237) DALYs, followed by smoking (7·10 million [6·83–7·37] deaths and 182 million [173–193] DALYs), high fasting plasma glucose (6·53 million [5·23–8·23] deaths and 171 million [144–201] DALYs), high body-mass index (BMI; 4·72 million [2·99–6·70] deaths and 148 million [98·6–202] DALYs), and short gestation for birthweight (1·43 million [1·36–1·51] deaths and 139 million [131–147] DALYs). In total, risk-attributable DALYs declined by 4·9% (3·3–6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. Interpretation: By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning.

KW - Adolescent

KW - Adult

KW - Age Distribution

KW - Aged

KW - Aged, 80 and over

KW - Child

KW - Child, Preschool

KW - Disabled Persons/statistics & numerical data

KW - Environmental Exposure/adverse effects

KW - Female

KW - Global Burden of Disease/statistics & numerical data

KW - Global Health/statistics & numerical data

KW - Health Risk Behaviors

KW - Humans

KW - Infant

KW - Infant, Newborn

KW - Life Expectancy

KW - Male

KW - Metabolic Diseases/epidemiology

KW - Middle Aged

KW - Occupational Diseases/epidemiology

KW - Occupational Exposure/adverse effects

KW - Quality-Adjusted Life Years

KW - Risk Assessment

KW - Sex Distribution

KW - Socioeconomic Factors

KW - Young Adult

UR - http://www.scopus.com/inward/record.url?scp=85056201749&partnerID=8YFLogxK

U2 - 10.1016/S0140-6736(18)32225-6

DO - 10.1016/S0140-6736(18)32225-6

M3 - Article

VL - 392

SP - 1923

EP - 1994

JO - Lancet

JF - Lancet

SN - 0140-6736

IS - 10159

ER -